Usefulness of Self-Selected Scenarios for Simple Triage and Rapid Treatment Method Using Virtual Reality.

BACKGROUND: Repeated triage training is necessary to maintain and improve the accuracy of simple triage and rapid treatment (START), a popular triage method. Virtual reality (VR) may be more effective than conventional training methods. This study aimed to verify the educational usefulness of START using VR originally developed for students. METHODS: A VR was initially developed with a function that allowed students to select the triage procedure and its evaluation. Triage was performed using a simple modified START method, and eight scenarios were developed. The participants included 70 paramedic students classified into VR and live lecture groups. They took a 20-question written test that evaluated their academic ability before the course. After the course, a practical test and a 20-question written test were conducted. The total score of the practical test was 43 points. Triage procedure (1 point), observation and evaluation (1-5 points), and triage categories (1 point) were evaluated in this test. RESULTS: The VR and live lecture groups consisted of 33 and 29 participants, respectively. No significant differences were observed pre- and post-test. In the practical test, the median (interquartile range) score was 29 (26-32) and 25 (23-29) for the VR and live lecture groups, respectively, with the VR group scoring significantly higher (P=0.03). CONCLUSION: Our results confirmed the educational usefulness of selective VR for active learning of START. Therefore, VR combined with live lectures and simulations would be an optimal educational technique.

Development of a Machine Learning Model to Predict Cardiac Arrest during Transport of Trauma Patients.

BACKGROUND: Trauma is a serious medical and economic burden worldwide, and patients with traumatic injuries have a poor survival rate after cardiac arrest. The authors developed a prediction model specific to prehospital trauma care and used machine learning techniques to increase its accuracy. METHODS: This retrospective observational study analyzed data from patients with blunt trauma injuries due to traffic accidents and falls from January 1, 2018, to December 31, 2019. The data were collected from the National Emergency Medical Services Information System, which stores emergency medical service activity records nationwide in the United States. A random forest algorithm was used to develop a machine learning model. RESULTS: The prediction model had an area under the curve of 0.95 and a negative predictive value of 0.99. The feature importance of the predictive model was highest for the AVPU (Alert, Verbal, Pain, Unresponsive) scale, followed by oxygen saturation (SpO2). Among patients who were progressing to cardiac arrest, the cutoff value was 89% for SpO2 in nonalert patients. CONCLUSIONS: The machine learning model was highly accurate in identifying patients who did not develop cardiac arrest.

A Study on Points of Respiratory Assist Devices Using in Pre-Hospital Care Respiratory Assist Devices in Pre-Hospital Care.

BACKGROUND: In Japan, increasing the number of ambulance requests, the case with the use of respiratory assistance devices in prehospital care by paramedics is also increasing1. When patient experiences respiratory failure, the first responders frequently select a respiratory assist device (RAD) such as Bag Valve Mask (BVM), Jackson Rees (JR), or BVM with Gas Supply Valve® (BVM+GSV). This is based on both evaluation and experience as there is no study indicating which RAD is the best choice at the pre-hospital emergency site. This study clarified the precautions when using BVM, JR, and BVM+GSV in pre-hospital emergency medical care with healthy volunteers. METHODS: Twenty healthy adults were fitted with a RAD while breathing spontaneously, and changes in vital signs and ETCO2 were observed. RESULTS: The level of ETCO2 became elevated after each RAD was attached. The value was significantly higher in the JR group than in the others. CONCLUSIONS: The study showed that even in the presence of spontaneous breathing, ETCO2 increased markedly with the application of respiratory assist devices that are used in pre-hospital care for conditions such as hypoxemia and ventilatory disturbance. The increase in ETCO2 was particularly significant in the JR group, suggesting the need for caution when selecting JRs for pre-hospital care. As the number of subjects was only 20 for each RAD, studies with a larger sample size are needed.

Accuracy of breathing and radial pulse assessment by non-medical persons: an observational cross-sectional study.

Early recognition of cardiopulmonary arrest (CPA) expedites emergency calls and resuscitation and improves the survival rate of unresponsive individuals. However, the accuracy of breathing and radial artery pulse assessment by non-medical persons is poorly understood. The aim of this study was to determine the accuracy of breathing assessment and radial pulse palpation among 450 non-medical personnel using a high-fidelity simulator. We examined the accuracy of 10 second's assessment for breathing and radial pulse using a high-fidelity mannequin simulator, included 496 non-medical participants (school teachers) between 2016-2018. For a primary results, the sensitivity for the detection of the presence of the breathing and radial pulse was 96.2% (97.5% for sensitivity and 92.0% for specificity) and 91.7% (99.1% for sensitivity and 56.8% for specificity), respectively. Futher, breathing rate and radial pulse rate were strongly correlated with the assessments, with Spearman's correlation coefficients of 0.813 (P < 0.001) and 0.719 (P < 0.001), respectively. In contrast, radial pulse strength was weakly correlated with the assessment (coefficient of 0.288, P < 0.001). Our results suggested that non-medical persons would show high accuracy in detecting and measuring respiration and radial pulse, although they did not accurately determine radial pulse strength for the early recognition of CPA.

Evaluation of outcomes after EMS-witnessed traumatic out-of-hospital cardiac arrest caused by traffic collisions.

AIM: The survival rate of patients with traumatic cardiac arrest is 3% or lower. Cardiac arrest witnessed by emergency medical services (EMS) accounts for approximately 16% of prehospital traumatic cardiac arrests, but the prognosis is unknown. We aimed to compare the 1-month survival rate of cardiac arrest witnessed by EMS with that of cardiac arrest witnessed by bystanders and unwitnessed cardiac arrest in traffic trauma victims; further, the time from injury to cardiac arrest was assessed. METHODS: This analysis used the Utstein Registry in Japan and included data of 3883 patients with traumatic cardiac arrest caused by traffic collisions registered between 2014 and 2019 in Japan. RESULTS: The 1-month survival rate was 10.9% in the EMS-witnessed cardiac arrest group; this was significantly higher than that in the bystander-witnessed (7.2%) and unwitnessed (5.6%) cardiac arrest groups (P < 0.01). The median time from injury to cardiac arrest was 18 min (25% quartile: 12, 75% quartile: 26). CONCLUSION: The 1-month survival rate was significantly higher in the EMS-witnessed cardiac arrest group than in the bystander-witnessed and unwitnessed cardiac arrest groups. It is important to prevent progression to cardiac arrest in trauma patients with intact respiratory function and pulse rate at the time of contact with EMS. A system for early recognition of severe trauma is needed, and a doctor's car or helicopter can be requested as needed. We believe that early recognition and prompt intervention will improve the prognosis of prehospital traumatic cardiac arrest.

Predictability of the Call Triage Protocol to Detect if Dispatchers Should Activate Community First Responders.

INTRODUCTION: Shortening response time to an emergency call leads to the success of resuscitation by chest compression and defibrillation. However, response by ambulance or fire truck is not fast enough for resuscitation in Japan. In rural areas, response times can be more than 10 minutes. One possible way to shorten the response time is to establish a system of first responders (eg, police officers or firefighters) who are trained appropriately to perform resuscitation. Another possible way is to use a system of Community First Responders (CFRs) who are trained neighbors. At present, there are no call triage protocols to decide if dispatchers should activate CFRs. OBJECTIVE: The aim of this study was to determine the predictability to detect if dispatchers should activate CFRs. METHODS: Two CFR call triage protocols (CFR protocol Ver.0 and Ver.1) were established. The predictability of CFR protocols was examined by comparing the paramedic field reports. From the results of sensitivity of CFR protocol, the numbers of annual CFR activations were calculated. All data were collected, prospectively, for four months from October 1, 2012 through January 31, 2013. RESULTS: The ROC-AUC values appear slightly higher in CFR protocol Ver.1 (0.857; 95% CI, 79.8-91.7) than in CFR protocol Ver.0 (0.847; 95% CI, 79.0-90.3). The number of annual CFR activations is higher in CFR protocol Ver.0 (7.47) than in CFR protocol Ver.1 (5.45). CONCLUSION: Two call triage protocols have almost the same predictability as the Medical Priority Dispatch System (MPDS). The study indicates that CFR protocol Ver.1 is better than CFR protocol Ver.0 because of the higher predictability and low number of activations. Also, it indicates that CFRs who are not medical professionals can respond to a patient with cardiac arrest.